Contraction aware parsing system for domain-specific languages

ABSTRACT

Aspects of the present invention disclose a method, computer program product, and system for parsing a domain-specific language (DSL) statement. The method includes one or more processors accessing a DSL statement that includes contracted phrases. The method further includes one or more processors identifying one or more contracted phrases in the DSL statement utilizing an annotated domain vocabulary for a DSL associated with the DSL statement and grammar rules for the DSL. The method further includes one or more processors determining expanded phrases corresponding to the identified one or more contracted phrases based on the annotated domain vocabulary and the grammar rules. The method further includes one or more processors creating an expanded abstract syntax tree (AST) that is representative of the DSL statement with the determined expanded phrases replacing the identified one or more contracted phrases.

STATEMENT ON PRIOR DISCLOSURES BY AN INVENTOR

Various aspects of the present invention have been disclosed in theproducts Decision Server Advanced Restricted V8.6, made publiclyavailable on Jun. 13, 2014. This disclosure is submitted under 35 U.S.C.102(b)(1)(A). The following documentation is provided in support of thedisclosure available on Jun. 13, 2014:

(i) IBM Support Portal, Decision Server Advanced Restricted V8.6Technotes; and

(ii) IBM Decision Server Insights V8.6 Installation Guide.

BACKGROUND OF THE INVENTION

The present invention relates generally to the field of domain-specificlanguages, and more particularly to parsing domain-specific languages.

A domain-specific language (DSL) is a computer language specialized to aparticular application domain. This is in contrast to a general-purposelanguage (GPL), which is broadly applicable across domains and lacksspecialized features for a particular domain. DSLs provide a convenientway to instrument applications and engines. There are a wide variety ofDSLs, ranging from widely used languages for common domains (e.g.,HyperText Markup Language (HTML) for web pages), down to languages usedby only a single piece of software. DSLs can be further subdivided bythe kind of language and include domain-specific markup languages,domain-specific modeling languages (more generally, specificationlanguages), and domain-specific programming languages. DSLs are capableof expressing complex condition-action rules and event-processing rules.The DSLs can support a rich domain vocabulary allowing the formulationof complex, nested expressions.

In computer science, an abstract syntax tree (AST), or syntax tree, is atree representation of the abstract syntactic structure of source codewritten in a programming language. Each node of the tree denotes aconstruct occurring in the source code. The syntax is “abstract” in notrepresenting every detail appearing in the real syntax. ASTs can also beused in program analysis and program transformation systems.

SUMMARY

Aspects of the present invention disclose a method, computer programproduct, and system for parsing a domain-specific language (DSL)statement. The method includes one or more processors accessing a DSLstatement that includes contracted phrases. The method further includesone or more processors identifying one or more contracted phrases in theDSL statement utilizing an annotated domain vocabulary for a DSLassociated with the DSL statement and grammar rules for the DSL. Themethod further includes one or more processors determining expandedphrases corresponding to the identified one or more contracted phrasesbased on the annotated domain vocabulary and the grammar rules. Themethod further includes one or more processors creating an expandedabstract syntax tree (AST) that is representative of the DSL statementwith the determined expanded phrases replacing the identified one ormore contracted phrases.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a functional block diagram of a data processing environment,in accordance with an embodiment of the present invention.

FIG. 2 is a flowchart depicting operational steps of a program fordetermining an expanded AST based on a domain-specific language (DSL)statement that includes contracted statements, in accordance with anembodiment of the present invention.

FIG. 3A is an example depiction of an object-role-modeling diagram for avocabulary of a DSL, in accordance with an embodiment of the presentinvention.

FIG. 3B is an example depiction of an object-role-modeling diagram foran extended vocabulary of a DSL, in accordance with an embodiment of thepresent invention.

FIGS. 4A and 4B are example depictions of an abstract syntax tree (AST),in accordance with an embodiment of the present invention.

FIG. 5 depicts a block diagram of components of a computing systemrepresentative of the client device and server of FIG. 1, in accordancewith an embodiment of the present invention.

DETAILED DESCRIPTION

Embodiments of the present invention allow for a method for parsingdomain-specific language (DSL) statements that is capable of recognizingcertain kinds of shortened and contracted expressions and to expand thecontracted into a form as prescribed by the DSL. A contracted DSLstatement is identified and utilized to create an abstract syntax tree(AST) that contains nodes that correspond to the contracted expressionsin the DSL statement. Then, the contracted AST is expanded into an ASTthat does not use contracted expressions and can be processed by anapplication or engine.

Some embodiments of the present invention recognize that expressivenessin DSL statements can lead to lengthy descriptions of rules, which canbe difficult to read and edit. Other embodiments recognize that an ASTthat is based off of a contracted DSL statement may not be compatiblewith the applications and engines that are associated with the DSL. Acontracted DSL statement is a DSL statement that includes shortened orcontracted expressions. For example, a comparison DSL statement of “theprice of the limousine is smaller than the price of the sports car” cancorrespond to contracted DSL statement of “the limousine is cheaper thanthe sports car.”

The present invention will now be described in detail with reference tothe Figures. FIG. 1 is a functional block diagram illustrating dataprocessing environment 100, in accordance with one embodiment of thepresent invention.

An embodiment of data processing environment 100 includes computingdevice 120 and server 130, interconnected over network 110. In anexample embodiment, computing device 120 can communicate with server130, via network 110, to send DSL statements to server 130 and accessinformation that is stored on server 130. In one embodiment, computingdevice 120 and server 130 communicate through network 110. Network 110can be, for example, a local area network (LAN), a telecommunicationsnetwork, a wide area network (WAN) such as the Internet, or anycombination of the three, and include wired, wireless, or fiber opticconnections. In general, network 110 can be any combination ofconnections and protocols that will support communications betweencomputing device 120 and server 130, in accordance with embodiments ofthe present invention.

In various embodiments of the present invention, computing device 120may be a workstation, personal computer, personal digital assistant,mobile phone, or any other device capable of executing computer readableprogram instructions, in accordance with embodiments of the presentinvention. In general, computing device 120 is representative of anyelectronic device or combination of electronic devices capable ofexecuting computer readable program instructions. Computing device 120may include components as depicted and described in further detail withrespect to FIG. 5, in accordance with embodiments of the presentinvention.

Computing device 120 includes application 122 and user interface 124.Application 122 is a software application that an individual utilizingcomputing device 120 can utilize (e.g., via user interface 124) tointerface with server 130. In one embodiment, computing device 120 sendsDSL statements to server 130 utilizing application 122.

User interface 124 is a program that provides an interface between auser of computing device 120 and a plurality of applications that resideon computing device 120. A user interface, such as user interface 124,refers to the information (such as graphic, text, and sound) that aprogram presents to a user and the control sequences the user employs tocontrol the program. A variety of types of user interfaces exist. In oneembodiment, user interface 124 is a graphical user interface. Agraphical user interface (GUI) is a type of user interface that allowsusers to interact with electronic devices, such as a computer keyboardand mouse, through graphical icons and visual indicators, such assecondary notation, as opposed to text-based interfaces, typed commandlabels, or text navigation. The actions in GUIs are often performedthrough direct manipulation of the graphical elements.

In example embodiments, server 130 can be a desktop computer, a computerserver, or any other computer systems known in the art. In certainembodiments, server 130 represents computer systems utilizing clusteredcomputers and components (e.g., database server computers, applicationserver computers, etc.) that act as a single pool of seamless resourceswhen accessed by elements of data processing environment 100 (e.g.,computing device 120). In general, server 130 is representative of anyelectronic device or combination of electronic devices capable ofexecuting computer readable program instructions. Server 130 may includecomponents as depicted and described in further detail with respect toFIG. 5, in accordance with embodiments of the present invention.

Server 130 includes vocabulary extender 132, DSL extender 134, DSLparser 136, storage device 140, and parsing program 200. Storage device140 includes vocabulary 142, grammar 144, and DSL statements 146.Storage device 140 can be implemented with any type of storage device,for example, persistent storage 508, which is capable of storing datathat may be accessed and utilized by server 130, such as a databaseserver, a hard disk drive, or a flash memory. In other embodiments,storage device 140 can represent multiple storage devices within server130.

Vocabulary extender 132 utilizes the vocabulary (e.g., vocabulary 142)of a DSL and annotations in the vocabulary to create an extendedvocabulary. In one embodiment, vocabulary extender 132 identifiesannotations in vocabulary 142 that are associated with operators in theDSL, which vocabulary extender 132 utilizes to create an extendedvocabulary. For example, vocabulary extender 132 identifies anannotation of “cheaper” associated with the type “car” attribute. Then,vocabulary extender 132 adds a derived operator of “cheaper” in thecreation of the extended vocabulary.

Vocabulary 142, stored in storage device 140, is associated with a DSLand includes words, phrases, their associated meanings, and other datathat the DSL utilizes. A domain vocabulary, such as vocabulary 142, is aset of terms to describe objects of a domain (e.g., associated with aDSL). Objects are instances of concepts such as ‘Car,’ ‘Color,’ ‘City,’‘Country.’ Each concept may have one or more attributes of given types,which are concepts or primitive types such as number or string. Forexample the concept ‘Car’ may have two attributes of type number, namely‘price’ and ‘speed,’ as well as an attribute ‘color’ of type ‘Color’.Each instance of a concept has a value for each attribute of theconcept. For example, the instance of concept ‘Car,’ named ‘the sportscar,’ has a value of ‘Green’ for the attribute ‘color.’ Additionally, aconcept may have operators that take instances of the concept asarguments and that result into values of a given primitive type such asnumber or Boolean (i.e. a type for the truth values true and false). Anexample is a containment operator that returns true if the citydescribed by a first argument of type ‘City’ is in the country describedby a second argument of type ‘Country,’ and that returns falseotherwise. A DSL may be based on a given vocabulary (e.g., vocabulary142) and contain expressions for the different vocabulary elements. Theexpressions can describe instances of concepts, attribute values of theinstances, and the results of applying operators from the vocabulary.

A vocabulary can be defined utilizing a graphical editor, a DSL fordefining vocabularies, an extensible markup language (XML) format, etc.Each of the annotations may be a text of a predefined form, whichdepends on the type of the contraction and which is associated to aconcept or attribute. For example, the attribute ‘price’ of concept‘Car’ may have the following annotation for defining the cheaper-thanoperator: “defines order ‘is cheaper than’ using ‘is less than’.”Similarly, the attribute ‘speed’ of concept ‘Car’ may have theannotation for defining the faster-than operator: “defines order ‘isfaster than’ using ‘is more than’.” Additional forms of contractions canbe specified by other forms of texts.

In an example embodiment, FIG. 3A depicts original vocabulary 310 for aDSL in the form of an object-role-modeling diagram. Original vocabulary310 depicts types of “car,” “number,” and “Boolean,” a binaryrelationship “price” between “car” and “number,” and a ternaryrelationship “is less than” between “number,” and “Boolean.” The pricerelationship has an annotation indicating that the relationshiprepresents a “cheaper” relationship over cars. Vocabulary extender 132utilizes the annotation and adds a ternary relationship between “car”and “Boolean,” creating extended vocabulary 350 (depicted in FIG. 3B).

In another example embodiment, FIG. 3B depicts extended vocabulary 350for a DSL in the form of an object-role-modeling diagram. Extendedvocabulary 350 depicts types of “car,” “number,” and “Boolean,” a binaryrelationship “price” between “car” and “number,” and a ternaryrelationship “is less than” between “number,” and “Boolean” (similarlyto original vocabulary 310). Extended vocabulary 350 includes a ternaryrelationship of “is cheaper than” between “car” and “Boolean” that isbased on the “cheaper” annotation in original vocabulary 310.

DSL extender 134 creates grammar rules for a vocabulary of a DSL, whichare added to the grammar of the DSL (e.g., grammar 144). Grammar 144,stored in storage device 140, is associated with a DSL and includesgrammar rules for statements in the DSL. The grammar of a DSL with avocabulary (e.g., grammar 144) may have a non-terminal symbol for eachconcept representing an expression that evaluates to an instance of theconcept. Grammar 144 may have grammar rules for formulating expressionsthat represent the attribute values or result of operations. In variousembodiments, the grammar rules for terms of vocabulary 142 can directlybe derived from vocabulary 142 in a generic way and need not bespecified explicitly. The grammar rules in grammar 144 that are derivedfrom a vocabulary extend the grammar (e.g., via DSL extender 134) of anordinary DSL without vocabulary.

In one embodiment, DSL extender 134 utilizes the extended vocabulary ofa DSL (created by vocabulary extender 132) and the grammar of a DSL(e.g., grammar 144) to determine and create grammar rules to add to thegrammar of the DSL. DSL extender 134 adds grammar rules to the grammarof the DSL (e.g., grammar 144) based on which parts of the vocabulary(e.g., vocabulary 142) are extended. In an example embodiment, a userdefines a vocabulary (e.g., vocabulary 142) utilizing a graphical editorthat has commands for declaring concepts, attributes, and operators. Bydefining such a vocabulary, the user is able to extend, (e.g., via DSLextender 134) a given rule language to a custom domain without needingto manually write new grammar rules. DSL extender 134 creates grammarrules to add to grammar 144 based on extended vocabulary 350. Extendedvocabulary 350 includes additional relationships (compared to originalvocabulary 310), and DSL extender 134 adds grammar rules to grammar 144corresponding to the additional relationships in extended vocabulary350.

Given a vocabulary (e.g., vocabulary 142) and an ordinary DSL that doesnot include a vocabulary, DSL extender 134 extends the grammar of theDSL by a grammar rule for each vocabulary element. For each concept ofthe vocabulary, DSL extender 134 generates a non-terminal symbol forexpressions that evaluate to instances of this concept. For example, DSLextender 134 generates the symbols <car>, <color>, <city>, <country> forthe expressions related to the concepts ‘Car,’ ‘Color,’ ‘City,’‘Country.’ These symbols complement existing non-terminal symbolsrepresenting primitive values such as numbers, Boolean truth values,strings, etc. In addition, DSL extender 134 generates grammar rules foraccessing attribute values. The left-hand side of such a rule is thenon-terminal system for the attribute type. The right-hand side consistsof an article, the attribute name as defined in the vocabulary, thepartitive article “of,” and the non-terminal system for the concept thatdeclares the attribute. For example, ‘<number>::=the price of <car>,’‘<number>::=the speed of <car>,’ and ‘<color>::=the color of <car>.’ Inadditional embodiments, DSL extender 134 generates grammar rules forapplying operators from the vocabulary. The left-hand side of such arule is the non-terminal system for the result type of the operator. Theright-hand side may use an infix notation and consist of the expressionfor the first argument, the operator symbol, and the expression for thesecond argument.

DSL parser 136 is a standard parsing program or application that iscapable of parsing DSL statements. DSL parser 136 utilizes the extendedgrammar of the DSL (e.g., from DSL extender 134), the extended DSLvocabulary (e.g., from vocabulary extender 132), and DSL statements,which can include contracted statements.

Parsing program 200 determines an expanded AST based on a DSL statementthat includes contracted statements, in accordance with embodiments ofthe present invention. In various embodiments, parsing program 200utilizes DSL parser 136 to parse DSL statements, in accordance withvarious embodiments of the present invention. In one embodiment, parsingprogram 200 utilizes DSL parser 136 to parse a DSL statement (e.g., astatement in DSL statements 146) that includes contractions, and parsingprogram 200 annotates the resulting AST nodes corresponding to thecontractions. DSL statements 146, stored in storage device 140, includesthe DSL statements that server 130 has received (e.g., from computingdevice 120).

FIG. 2 is a flowchart depicting operational steps of parsing program200, a program for determining an expanded AST based on a DSL statementthat includes contracted statements, in accordance with embodiments ofthe present invention.

In step 202, parsing program 200 identifies a DSL statement. In oneembodiment, parsing program 200 accesses and identifies a DSL statementfrom DSL statements 146, stored in storage device 140. In anotherembodiment, parsing program 200 identifies a DSL statement received fromcomputing device 120.

In decision step 204, parsing program 200 determines whether theidentified DSL statement is a contracted statement. In one embodiment,parsing program 200 determines whether a DSL statement (identified instep 202) includes contractions and/or shortened phrases (e.g.,utilizing semantic annotations). In another embodiment, parsing program200 receives an indication that the DSL statement is a contractedstatement. In response to determining that the identified DSL statementis not a contracted statement (decision step 204, “no” branch), parsingprogram 200 returns to step 202. In an example, parsing program 200identifies a DSL statement of “the limousine is cheaper than the sportscar” (in step 202). Then, parsing program 200 analyzes the identifiedDSL statement utilizing semantic annotations of vocabulary 142 anddetermines that the identified DSL statement is a contracted statement(decision step 204, “yes” branch). In this example, parsing program 200identifies “is cheaper than” as a contracted phrase in the identifiedDSL statement.

In step 206, parsing program 200 creates an AST that represents thecontracted DSL statement. More specifically, in response to determiningthat the identified DSL statement is a contracted statement (decisionstep 204, “yes” branch), parsing program 200 creates an AST thatrepresents the contracted DSL statement (identified in step 202). In oneembodiment, parsing program 200 utilizes DSL extender 134 and grammar144 (including grammar extensions) to parse the identified DSL statement(identified in step 202 and determined to be a contracted statement indecision step 204) and create an AST that represents the DSL statement.In an example embodiment, FIG. 4A depicts contracted AST 400. Parsingprogram 200 creates contracted AST (in step 206) based on the contractedidentified DSL statement of “the limousine is cheaper than the sportscar.” Parsing program 200 utilizes annotations and extensions invocabulary 142 to include an annotation that indicates the contractionof the node in the AST corresponding to “is cheaper than” with theannotation of “compares ‘the price of . . . ’” in contracted AST 400.The annotation provides an indication (from vocabulary 142) that thecontraction in contracted AST 400 is associated with a price operator.

In step 208, parsing program 200 identifies contractions in the nodes ofthe created AST. In one embodiment, parsing program 200 identifies oneor more contractions in the created AST (created in step 206). Forexample, parsing program 200 utilizes semantic annotations (e.g.,provided in vocabulary 142) to identify contracted phrases (e.g.,shortened forms of phrases in a DSL statement). In an example, parsingprogram 200 analyzes contracted AST 400 (depicted in FIG. 4A) andutilizes the sematic annotation of “compares ‘the price of . . . ’” toidentify that the corresponding AST node of “is cheaper than” is acontracted phrase. In various embodiments, parsing program 200 canidentify a plurality of contractions in an AST in a plurality oflocations within the AST.

In step 210, parsing program 200 creates an updated AST. In oneembodiment, parsing program 200 creates an updated AST that resolves andexpands the identified contractions (from step 208). In an exampleembodiment, when resolving contractions, parsing program 200 applies thesemantic annotations that correspond to the nodes in the AST thatinclude a contracted phrase. The annotations facilitate expansion of theAST into an expanded AST, in which the identified contractions (fromstep 208) are expanded. Parsing program 200 replaces the identifiedcontractions in the AST by expanding the contractions according tovocabulary 142, which results in an updated, expanded AST. For example,parsing program 200 utilizes the semantic annotation of “compares ‘theprice of . . . ’” on the node in contracted AST 400 of “is cheaperthan,” vocabulary 142, and grammar 144 to create an expanded AST. FIG.4B depicts expanded AST 450, which is a contraction-free AST. In anexample embodiment, parsing program 200 processes contracted AST 400,expands the contractions in contracted AST 400, and utilizes theexpanded contractions to create expanded AST 450. In this exampleembodiment, expanded AST 450 is representative of a DST statement of“the price of the limousine is less than the price of the sports car.”In various embodiments, parsing program 200 creates an AST (e.g.,expanded AST 450) that is capable of being utilized by the applicationsand/or engines associated with the DSL.

In decision step 212, parsing program 200 determines whether additionalcontractions are present in the updated AST. In one embodiment, parsingprogram 200 analyzes (e.g., utilizing semantic annotations) the updatedAST (created in step 210) to determine whether the updated AST includesany additional contracted phrases. In various embodiments, if theoriginal AST (e.g., created in step 206) included contractions withincontractions (e.g., composed contractions or nested contractions), thenparsing program 200 can determine that the updated AST does stillinclude one or more contractions (decision step 212, “yes” branch). Inresponse to determining that the updated AST does include one or moreadditional contractions, parsing program 200 returns to step 208.

In step 214, parsing program 200 stores the updates AST. In oneembodiment, in response to determining that no additional contractionsare present in the updates AST (decision step 212, “no” branch), parsingprogram 200 stores the updated AST (e.g., in storage device 140). Thestored AST is capable of being accessed and utilized by desiredapplications of systems. In another embodiment, parsing program 200sends the updates AST a corresponding application for processing.

In a first example embodiment, a concept such as a “car” may have anattribute “price” of a type integer. Grammar 144 can include aconstruction for comparing two expressions of type integers (e.g.,<expr> is less than <expr>). Given two cars called “limousine” and“sports car” in vocabulary 142, the corresponding DSL is capable ofaccepting a DSL statement of “the price of the limousine is smaller thanthe price of the sports car.” Vocabulary 142 and grammar 144 includeinformation that permits a semantic annotation of the attribute “price”to indicate that the price attribute represents an order called“cheaper” on cars, which permits a contracted phrase of “the limousineis cheaper than the sports car.” Parsing program 200 uses the semanticannotation to recognize the contraction and produce an AST (e.g.,expanded AST 450) corresponding to the expanded DSL statement (i.e.,“the price of the limousine is smaller than the price of the sportscar”).

In a second example embodiment, a concept such as “event” may have anattribute “time” representing points in time. Grammar 144 can include aconstruction for comparing two points in time, and the corresponding DSLis capable of accepting a DSL statement of “the time of the computerpurchase event is before the time of the car purchase event.” Vocabulary142 and grammar 144 include information that permits a semanticannotation of the concept “event” to indicate that the attribute “time”defines a temporal aspect of the concept, which permits an expression oftype “event” can be used where a time point is expected. In thisembodiment, “the computer purchase event is before the car purchaseevent” is a potential contracted DSL statement. Parsing program 200utilizes the semantic annotation to recognize the contraction andproduce an AST corresponding to the expanded DSL statement (i.e., “thetime of the computer purchase event is before the time of the carpurchase event”).

In a third example embodiment, vocabulary 142 can provide attributes fordirect relationships (e.g., ownership relationships, transitivepossessive relationships, etc.). Indirect relationships can be expressedby paths and statements that can be verbose, for example, “the city ofthe address of the shop of the purchase event is in the United Kingdom.”If vocabulary 142 and grammar 144 include a unique path from the sourceconcept “purchase event” to the target concept “address,” then the DSLstatement can be contracted. In this example, the DSL statement can becontracted to “the city of the purchase event is in the United Kingdom.”Parsing program 200 can recognize the contraction utilizing grammarrules for attribute accesses in grammar 144. In additional embodiments,different forms of contractions (e.g., temporal relationships, directrelationships, etc.) can be combined together.

FIG. 5 depicts a block diagram of components of computer 500, which isrepresentative of client device 120 and server 130, in accordance withan illustrative embodiment of the present invention. It should beappreciated that FIG. 5 provides only an illustration of oneimplementation and does not imply any limitations with regard to theenvironments in which different embodiments may be implemented. Manymodifications to the depicted environment may be made.

Computer 500 includes communications fabric 502, which providescommunications between computer processor(s) 504, memory 506, persistentstorage 508, communications unit 510, and input/output (I/O)interface(s) 512. Communications fabric 502 can be implemented with anyarchitecture designed for passing data and/or control informationbetween processors (such as microprocessors, communications and networkprocessors, etc.), system memory, peripheral devices, and any otherhardware components within a system. For example, communications fabric502 can be implemented with one or more buses.

Memory 506 and persistent storage 508 are computer readable storagemedia. In this embodiment, memory 506 includes random access memory(RAM) 514 and cache memory 516. In general, memory 506 can include anysuitable volatile or non-volatile computer readable storage media.Software and data 522 are stored in persistent storage 508 for accessand/or execution by processors 504 via one or more memories of memory506. With respect to client device 120, software and data 522 includesapplication 122. With respect to server 130, software and data 522includes vocabulary 132, DSL extender 134, DSL parser 136, parsingprogram 200, vocabulary 142, grammar 144, and DSL statements 146.

In this embodiment, persistent storage 508 includes a magnetic hard diskdrive. Alternatively, or in addition to a magnetic hard disk drive,persistent storage 508 can include a solid state hard drive, asemiconductor storage device, read-only memory (ROM), erasableprogrammable read-only memory (EPROM), flash memory, or any othercomputer readable storage media that is capable of storing programinstructions or digital information.

The media used by persistent storage 508 may also be removable. Forexample, a removable hard drive may be used for persistent storage 508.Other examples include optical and magnetic disks, thumb drives, andsmart cards that are inserted into a drive for transfer onto anothercomputer readable storage medium that is also part of persistent storage508.

Communications unit 510, in these examples, provides for communicationswith other data processing systems or devices. In these examples,communications unit 510 may include one or more network interface cards.Communications unit 510 may provide communications through the use ofeither or both physical and wireless communications links. Software anddata 522 may be downloaded to persistent storage 508 throughcommunications unit 510.

I/O interface(s) 512 allows for input and output of data with otherdevices that may be connected to computer 500. For example, I/Ointerface 512 may provide a connection to external devices 518 such as akeyboard, keypad, a touch screen, and/or some other suitable inputdevice. External devices 518 can also include portable computer readablestorage media such as, for example, thumb drives, portable optical ormagnetic disks, and memory cards. Software and data 522 can be stored onsuch portable computer readable storage media and can be loaded ontopersistent storage 508 via I/O interface(s) 512. I/O interface(s) 512also can connect to a display 520.

Display 520 provides a mechanism to display data to a user and may be,for example, a computer monitor. Display 520 can also function as atouch screen, such as a display of a tablet computer.

The programs described herein are identified based upon the applicationfor which they are implemented in a specific embodiment of theinvention. However, it should be appreciated that any particular programnomenclature herein is used merely for convenience, and thus theinvention should not be limited to use solely in any specificapplication identified and/or implied by such nomenclature.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the invention.The terminology used herein was chosen to best explain the principles ofthe embodiment, the practical application or technical improvement overtechnologies found in the marketplace, or to enable others of ordinaryskill in the art to understand the embodiments disclosed herein.

What is claimed is:
 1. A method for parsing a domain-specific language(DSL) statement, the method comprising: accessing, by one or moreprocessors, a DSL statement that includes contracted phrases;identifying, by one or more processors, one or more contracted phrasesin the DSL statement utilizing an annotated domain vocabulary for a DSLassociated with the DSL statement and grammar rules for the DSL;determining, by one or more processors, expanded phrases correspondingto the identified one or more contracted phrases based on the annotateddomain vocabulary and the grammar rules; and creating, by one or moreprocessors, an expanded abstract syntax tree (AST) that isrepresentative of the DSL statement with the determined expanded phrasesreplacing the identified one or more contracted phrases.
 2. The methodof claim 1, wherein the identifying one or more contracted phrases inthe DSL statement utilizing the annotated domain vocabulary for the DSLassociated with the DSL statement and grammar rules for the DSLcomprises: creating, by one or more processors, an AST that isrepresentative of the DSL statement that includes contracted phrases;and identifying, by one or more processors, one or more contractedphrases in the created AST utilizing the annotated domain vocabulary forthe DSL and the grammar rules for the DSL.
 3. The method of claim 2,wherein the created AST includes semantic annotations that correspond tonodes in the created AST that include a contracted phrase.
 4. The methodof claim 1, further comprising: determining, by one or more processors,whether the expanded AST includes any contracted phrases; and responsiveto determining that the expanded AST does include contracted phrases,identifying, by one or more processors, one or more contracted phrasesin the expanded AST utilizing the annotated domain vocabulary for theDSL and the grammar rules for the DSL.
 5. The method of claim 1, whereinthe determining expanded phrases corresponding to the identified one ormore contracted phrases based on the annotated domain vocabulary and thegrammar rules, further comprises: expanding, by one or more processors,the one or more identified contracted phrases according to the domainvocabulary for the DSL.
 6. The method of claim 1, further comprising:identifying, by one or more processors, operators in the DSL statementthat are associated with annotations in the annotated domain vocabulary;and determining, by one or more processors, extensions to add to theannotated domain vocabulary based on the identified operators.
 7. Themethod of claim 6, further comprising: determining, by one or moreprocessors, one or more rules to add to the grammar rules for the DSLbased on the determined extensions to add to the annotated domainvocabulary.
 8. A computer program product for parsing a domain-specificlanguage (DSL) statement, the computer program product comprising: oneor more computer readable storage media and program instructions storedon the one or more computer readable storage media, the programinstructions comprising: program instructions to access a DSL statementthat includes contracted phrases; program instructions to identify oneor more contracted phrases in the DSL statement utilizing an annotateddomain vocabulary for a DSL associated with the DSL statement andgrammar rules for the DSL; program instructions to determine expandedphrases corresponding to the identified one or more contracted phrasesbased on the annotated domain vocabulary and the grammar rules; andprogram instructions to create an expanded abstract syntax tree (AST)that is representative of the DSL statement with the determined expandedphrases replacing the identified one or more contracted phrases.
 9. Thecomputer program product of claim 8, wherein the program instructions toidentify one or more contracted phrases in the DSL statement utilizingthe annotated domain vocabulary for the DSL associated with the DSLstatement and grammar rules for the DSL comprise program instructionsto: create an AST that is representative of the DSL statement thatincludes contracted phrases; and identify one or more contracted phrasesin the created AST utilizing the annotated domain vocabulary for the DSLand the grammar rules for the DSL.
 10. The computer program product ofclaim 9, wherein the created AST includes semantic annotations thatcorrespond to nodes in the created AST that include a contracted phrase.11. The computer program product of claim 8, further comprising programinstructions, stored on the one or more computer readable storage media,to: determine whether the expanded AST includes any contracted phrases;and responsive to determining that the expanded AST does includecontracted phrases, identify one or more contracted phrases in theexpanded AST utilizing the annotated domain vocabulary for the DSL andthe grammar rules for the DSL.
 12. The computer program product of claim8, wherein the program instructions to determine expanded phrasescorresponding to the identified one or more contracted phrases based onthe annotated domain vocabulary and the grammar rules, further compriseprogram instructions to: expand the one or more identified contractedphrases according to the domain vocabulary for the DSL.
 13. The computerprogram product of claim 8, further comprising program instructions,stored on the one or more computer readable storage media, to: identifyoperators in the DSL statement that are associated with annotations inthe annotated domain vocabulary; and determine extensions to add to theannotated domain vocabulary based on the identified operators.
 14. Thecomputer program product of claim 13, further comprising programinstructions, stored on the one or more computer readable storage media,to: determine one or more rules to add to the grammar rules for the DSLbased on the determined extensions to add to the annotated domainvocabulary.
 15. A computer system parsing a domain-specific language(DSL) statement, the computer system comprising: one or more computerprocessors; one or more computer readable storage media; and programinstructions stored on the computer readable storage media for executionby at least one of the one or more processors, the program instructionscomprising: program instructions to access a DSL statement that includescontracted phrases; program instructions to identify one or morecontracted phrases in the DSL statement utilizing an annotated domainvocabulary for a DSL associated with the DSL statement and grammar rulesfor the DSL; program instructions to determine expanded phrasescorresponding to the identified one or more contracted phrases based onthe annotated domain vocabulary and the grammar rules; and programinstructions to create an expanded abstract syntax tree (AST) that isrepresentative of the DSL statement with the determined expanded phrasesreplacing the identified one or more contracted phrases.
 16. Thecomputer system of claim 15, wherein the program instructions toidentify one or more contracted phrases in the DSL statement utilizingthe annotated domain vocabulary for the DSL associated with the DSLstatement and grammar rules for the DSL comprise program instructionsto: create an AST that is representative of the DSL statement thatincludes contracted phrases; and identify one or more contracted phrasesin the created AST utilizing the annotated domain vocabulary for the DSLand the grammar rules for the DSL.
 17. The computer system of claim 15,further comprising program instructions, stored on the computer readablestorage media for execution by at least one of the one or moreprocessors, to: determine whether the expanded AST includes anycontracted phrases; and responsive to determining that the expanded ASTdoes include contracted phrases, identify one or more contracted phrasesin the expanded AST utilizing the annotated domain vocabulary for theDSL and the grammar rules for the DSL.
 18. The computer system of claim15, wherein the program instructions to determine expanded phrasescorresponding to the identified one or more contracted phrases based onthe annotated domain vocabulary and the grammar rules, further compriseprogram instructions to: expand the one or more identified contractedphrases according to the domain vocabulary for the DSL.
 19. The computersystem of claim 15, further comprising program instructions, stored onthe computer readable storage media for execution by at least one of theone or more processors, to: identify operators in the DSL statement thatare associated with annotations in the annotated domain vocabulary; anddetermine extensions to add to the annotated domain vocabulary based onthe identified operators.
 20. The computer system of claim 19, furthercomprising program instructions, stored on the computer readable storagemedia for execution by at least one of the one or more processors, to:determine one or more rules to add to the grammar rules for the DSLbased on the determined extensions to add to the annotated domainvocabulary.